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2.
Lancet Diabetes Endocrinol ; 9(10): 671-680, 2021 10.
Article in English | MEDLINE | ID: covidwho-1531932

ABSTRACT

BACKGROUND: Diabetic ketoacidosis (DKA) has been reported to be increasing in frequency during the COVID-19 pandemic. We aimed to examine the rates of DKA hospital admissions and the patient demographics associated with DKA during the pandemic compared with in prepandemic years. METHODS: Using a comprehensive, multiethnic, national dataset, the Secondary Uses Service repository, we extracted all emergency hospital admissions in England coded with DKA from March 1 to June 30, 2020 (first wave of the pandemic), July 1 to Oct 31, 2020 (post-first wave), and Nov 1, 2020, to Feb 28, 2021 (second wave), and compared these with DKA admissions in the equivalent periods in 2017-20. We also examined baseline characteristics, mortality, and trends in patients who were admitted with DKA. FINDINGS: There were 8553 admissions coded with DKA during the first wave, 8729 during the post-first wave, and 10 235 during the second wave. Compared with preceding years, DKA admissions were 6% (95% CI 4-9; p<0·0001) higher in the first wave of the pandemic (from n=8048), 6% (3-8; p<0·0001) higher in the post-first wave (from n=8260), and 7% (4-9; p<0·0001) higher in the second wave (from n=9610). In the first wave, DKA admissions reduced by 19% (95% CI 16-21) in those with pre-existing type 1 diabetes (from n=4965 to n=4041), increased by 41% (35-47) in those with pre-existing type 2 diabetes (from n=2010 to n=2831), and increased by 57% (48-66) in those with newly diagnosed diabetes (from n=1072 to n=1681). Compared with prepandemic, type 2 diabetes DKA admissions were similarly common in older individuals and men but were higher in those of non-White ethnicities during the first wave. The increase in newly diagnosed DKA admissions occurred across all age groups and these were significantly increased in men and people of non-White ethnicities. In the post-first wave, DKA admissions did not return to the baseline level of previous years; DKA admissions were 14% (11-17) lower in patients with type 1 diabetes (from n=5208 prepandemic to n=4491), 30% (24-36) higher in patients with type 2 diabetes (from n=2011 to n=2613), and 56% (47-66) higher in patients with newly diagnosed diabetes (from n=1041 to n=1625). During the second wave, DKA admissions were 25% (22-27) lower in patients with type 1 diabetes (from n=5769 prepandemic to n=4337), 50% (44-56) higher in patients with type 2 diabetes (from n=2608 to n=3912), and 61% (52-70) higher in patients with newly diagnosed diabetes (from n=1234 to n=1986). INTERPRETATION: Our results provide evidence for differences in the numbers and characteristics of people presenting with DKA during the COVID-19 pandemic compared with in the preceding 3 years. Greater awareness of risk factors for DKA in type 2 diabetes and vigilance for newly diagnosed diabetes presenting with DKA during the COVID-19 pandemic might help mitigate the increased impact of DKA. FUNDING: None.


Subject(s)
COVID-19/epidemiology , Diabetes Mellitus, Type 2/epidemiology , Diabetic Ketoacidosis/epidemiology , Emergency Service, Hospital/trends , Patient Admission/trends , Population Surveillance , Adolescent , Adult , Aged , COVID-19/prevention & control , Databases, Factual/trends , Diabetes Mellitus, Type 2/therapy , Diabetic Ketoacidosis/therapy , England/epidemiology , Female , Humans , Male , Middle Aged , Population Surveillance/methods , Time Factors , Young Adult
3.
Lancet Diabetes Endocrinol ; 9(5): 293-303, 2021 05.
Article in English | MEDLINE | ID: covidwho-1531930

ABSTRACT

BACKGROUND: In patients with type 2 diabetes, hyperglycaemia is an independent risk factor for COVID-19-related mortality. Associations between pre-infection prescription for glucose-lowering drugs and COVID-19-related mortality in people with type 2 diabetes have been postulated but only investigated in small studies and limited to a few agents. We investigated whether there are associations between prescription of different classes of glucose-lowering drugs and risk of COVID-19-related mortality in people with type 2 diabetes. METHODS: This was a nationwide observational cohort study done with data from the National Diabetes Audit for people with type 2 diabetes and registered with a general practice in England since 2003. Cox regression was used to estimate the hazard ratio (HR) of COVID-19-related mortality in people prescribed each class of glucose-lowering drug, with covariate adjustment with a propensity score to address confounding by demographic, socioeconomic, and clinical factors. FINDINGS: Among the 2 851 465 people with type 2 diabetes included in our analyses, 13 479 (0·5%) COVID-19-related deaths occurred during the study period (Feb 16 to Aug 31, 2020), corresponding to a rate of 8·9 per 1000 person-years (95% CI 8·7-9·0). The adjusted HR associated with recorded versus no recorded prescription was 0·77 (95% CI 0·73-0·81) for metformin and 1·42 (1·35-1·49) for insulin. Adjusted HRs for prescription of other individual classes of glucose-lowering treatment were as follows: 0·75 (0·48-1·17) for meglitinides, 0·82 (0·74-0·91) for SGLT2 inhibitors, 0·94 (0·82-1·07) for thiazolidinediones, 0·94 (0·89-0·99) for sulfonylureas, 0·94 (0·83-1·07) for GLP-1 receptor agonists, 1·07 (1·01-1·13) for DPP-4 inhibitors, and 1·26 (0·76-2·09) for α-glucosidase inhibitors. INTERPRETATION: Our results provide evidence of associations between prescription of some glucose-lowering drugs and COVID-19-related mortality, although the differences in risk are small and these findings are likely to be due to confounding by indication, in view of the use of different drug classes at different stages of type 2 diabetes disease progression. In the context of the COVID-19 pandemic, there is no clear indication to change prescribing of glucose-lowering drugs in people with type 2 diabetes. FUNDING: None.


Subject(s)
COVID-19/mortality , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/drug therapy , Hypoglycemic Agents/adverse effects , Aged , COVID-19/complications , Cohort Studies , England , Female , Humans , Male , Middle Aged , Proportional Hazards Models
7.
PLoS Med ; 18(11): e1003823, 2021 11.
Article in English | MEDLINE | ID: covidwho-1504361

ABSTRACT

BACKGROUND: Healthcare workers (HCWs) and ethnic minority groups are at increased risk of COVID-19 infection and adverse outcomes. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination is now available for frontline UK HCWs; however, demographic/occupational associations with vaccine uptake in this cohort are unknown. We sought to establish these associations in a large UK hospital workforce. METHODS AND FINDINGS: We conducted cross-sectional surveillance examining vaccine uptake amongst all staff at University Hospitals of Leicester NHS Trust. We examined proportions of vaccinated staff stratified by demographic factors, occupation, and previous COVID-19 test results (serology/PCR) and used logistic regression to identify predictors of vaccination status after adjustment for confounders. We included 19,044 HCWs; 12,278 (64.5%) had received SARS-CoV-2 vaccination. Compared to White HCWs (70.9% vaccinated), a significantly smaller proportion of ethnic minority HCWs were vaccinated (South Asian, 58.5%; Black, 36.8%; p < 0.001 for both). After adjustment for age, sex, ethnicity, deprivation, occupation, SARS-CoV-2 serology/PCR results, and COVID-19-related work absences, factors found to be negatively associated with vaccine uptake were younger age, female sex, increased deprivation, pregnancy, and belonging to any non-White ethnic group (Black: adjusted odds ratio [aOR] 0.30, 95% CI 0.26-0.34, p < 0.001; South Asian: aOR 0.67, 95% CI 0.62-0.72, p < 0.001). Those who had previously had confirmed COVID-19 (by PCR) were less likely to be vaccinated than those who had tested negative. Limitations include data being from a single centre, lack of data on staff vaccinated outside the hospital system, and that staff may have taken up vaccination following data extraction. CONCLUSIONS: Ethnic minority HCWs and those from more deprived areas as well as younger staff and female staff are less likely to take up SARS-CoV-2 vaccination. These findings have major implications for the delivery of SARS-CoV-2 vaccination programmes, in HCWs and the wider population, and should inform the national vaccination programme to prevent the disparities of the pandemic from widening.


Subject(s)
COVID-19 Vaccines/pharmacology , COVID-19/prevention & control , Health Personnel/statistics & numerical data , SARS-CoV-2/pathogenicity , Vaccination/statistics & numerical data , COVID-19/epidemiology , Delivery of Health Care/statistics & numerical data , Humans , Minority Groups , United Kingdom/epidemiology
8.
Health Systems and Policy Analysis|Policy brief 39 ; 2021.
Article in English | WHOIRIS, Grey literature | ID: grc-749808

ABSTRACT

This brief’s key messages are:COVID-19 can cause persistent ill-health. Around a quarter of people who have had the virus experience symptoms that continue for at least a month but one in 10 are still unwell after 12 weeks. This has been described by patient groups as “Long COVID”. Our understanding of how to diagnose and manage Long COVID is still evolving but the condition can be very debilitating. It is associated with a range of overlapping symptoms including generalized chest and muscle pain, fatigue, shortness of breath, and cognitive dysfunction, and the mechanisms involved affect multiple system and include persisting inflammation, thrombosis, and autoimmunity. It can affect anyone, but women and health care workers seem to be at greater risk. Long COVID has a serious impact on people’s ability to go back to work or have a social life. It affects their mental health and may have significant economic consequences for them, their families and for society. Policy responses need to take account of the complexity of Long COVID and how what is known about it is evolving rapidly. Areas to address include: The need for multidisciplinary, multispecialty approaches to assessment and management;Development, in association with patients and their families, of new care pathways and contextually appropriate guidelines for health professionals, especially in primary care to enable case management to be tailored to the manifestations of disease and involvement of different organ systems;The creation of appropriate services, including rehabilitation and online support tools;Action to tackle the wider consequences of Long COVID, including attention to employment rights, sick pay policies, and access to benefit and disability benefit packages;Involving patients both to foster self-care and self-help and in shaping awareness of Long COVID and the service (and research) needs it generates;and implementing well-functioning patient registers and other surveillance systems;creating cohorts of patients;and following up those affected as a means to support the research which is so critical to understanding and treating Long COVID.

9.
BMJ ; 375: e066768, 2021 11 03.
Article in English | MEDLINE | ID: covidwho-1501690

ABSTRACT

OBJECTIVE: To estimate the changes in life expectancy and years of life lost in 2020 associated with the covid-19 pandemic. DESIGN: Time series analysis. SETTING: 37 upper-middle and high income countries or regions with reliable and complete mortality data. PARTICIPANTS: Annual all cause mortality data from the Human Mortality Database for 2005-20, harmonised and disaggregated by age and sex. MAIN OUTCOME MEASURES: Reduction in life expectancy was estimated as the difference between observed and expected life expectancy in 2020 using the Lee-Carter model. Excess years of life lost were estimated as the difference between the observed and expected years of life lost in 2020 using the World Health Organization standard life table. RESULTS: Reduction in life expectancy in men and women was observed in all the countries studied except New Zealand, Taiwan, and Norway, where there was a gain in life expectancy in 2020. No evidence was found of a change in life expectancy in Denmark, Iceland, and South Korea. The highest reduction in life expectancy was observed in Russia (men: -2.33, 95% confidence interval -2.50 to -2.17; women: -2.14, -2.25 to -2.03), the United States (men: -2.27, -2.39 to -2.15; women: -1.61, -1.70 to -1.51), Bulgaria (men: -1.96, -2.11 to -1.81; women: -1.37, -1.74 to -1.01), Lithuania (men: -1.83, -2.07 to -1.59; women: -1.21, -1.36 to -1.05), Chile (men: -1.64, -1.97 to -1.32; women: -0.88, -1.28 to -0.50), and Spain (men: -1.35, -1.53 to -1.18; women: -1.13, -1.37 to -0.90). Years of life lost in 2020 were higher than expected in all countries except Taiwan, New Zealand, Norway, Iceland, Denmark, and South Korea. In the remaining 31 countries, more than 222 million years of life were lost in 2020, which is 28.1 million (95% confidence interval 26.8m to 29.5m) years of life lost more than expected (17.3 million (16.8m to 17.8m) in men and 10.8 million (10.4m to 11.3m) in women). The highest excess years of life lost per 100 000 population were observed in Bulgaria (men: 7260, 95% confidence interval 6820 to 7710; women: 3730, 2740 to 4730), Russia (men: 7020, 6550 to 7480; women: 4760, 4530 to 4990), Lithuania (men: 5430, 4750 to 6070; women: 2640, 2310 to 2980), the US (men: 4350, 4170 to 4530; women: 2430, 2320 to 2550), Poland (men: 3830, 3540 to 4120; women: 1830, 1630 to 2040), and Hungary (men: 2770, 2490 to 3040; women: 1920, 1590 to 2240). The excess years of life lost were relatively low in people younger than 65 years, except in Russia, Bulgaria, Lithuania, and the US where the excess years of life lost was >2000 per 100 000. CONCLUSION: More than 28 million excess years of life were lost in 2020 in 31 countries, with a higher rate in men than women. Excess years of life lost associated with the covid-19 pandemic in 2020 were more than five times higher than those associated with the seasonal influenza epidemic in 2015.


Subject(s)
COVID-19/mortality , Developed Countries/statistics & numerical data , Global Health/trends , Life Expectancy/trends , Mortality, Premature/trends , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Databases, Factual , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Young Adult
10.
Diabetes Care ; 2021 Oct 28.
Article in English | MEDLINE | ID: covidwho-1496877

ABSTRACT

BACKGROUND: This review was commissioned by the World Health Organization and presents a summary of the latest research evidence on the impact of coronavirus disease 2019 (COVID-19) on people with diabetes (PWD). PURPOSE: To review the evidence regarding the extent to which PWD are at increased risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and/or of suffering its complications, including associated mortality. DATA SOURCES: We searched the Cochrane COVID-19 Study Register, Embase, MEDLINE, and LitCOVID on 3 December 2020. STUDY SELECTION: Systematic reviews synthesizing data on PWD exposed to SARS-CoV-2 infection, reporting data on confirmed SARS-CoV-2 infection, admission to hospital and/or to intensive care unit (ICU) with COVID-19, and death with COVID-19 were used. DATA EXTRACTION: One reviewer appraised and extracted data; data were checked by a second. DATA SYNTHESIS: Data from 112 systematic reviews were narratively synthesized and displayed using effect direction plots. Reviews provided consistent evidence that diabetes is a risk factor for severe disease and death from COVID-19. Fewer data were available on ICU admission, but where available, these data also signaled increased risk. Within PWD, higher blood glucose levels both prior to and during COVID-19 illness were associated with worse COVID-19 outcomes. Type 1 diabetes was associated with worse outcomes than type 2 diabetes. There were no appropriate data for discerning whether diabetes was a risk factor for acquiring SARS-CoV-2 infection. LIMITATIONS: Due to the nature of the review questions, the majority of data contributing to included reviews come from retrospective observational studies. Reviews varied in the extent to which they assessed risk of bias. CONCLUSIONS: There are no data on whether diabetes predisposes to infection with SARS-CoV-2. Data consistently show that diabetes increases risk of severe COVID-19. As both diabetes and worse COVID-19 outcomes are associated with socioeconomic disadvantage, their intersection warrants particular attention.

11.
Ther Adv Endocrinol Metab ; 12: 20420188211054686, 2021.
Article in English | MEDLINE | ID: covidwho-1496096

ABSTRACT

Over time, various guidelines have emphasised the importance of physical activity and exercise training in the management of type 2 diabetes, chronic diseases, including cardiovascular disease and musculoskeletal disorders. The aim of this review is to evaluate the effectiveness of physical activity in people with type 2 diabetes and COVID-19. Most research to date indicates that people with type 2 diabetes who engage in both aerobic and resistance exercise see the greatest improvements in insulin sensitivity. Physical activity is now also known to be effective at reducing hospitalisation rates of respiratory viral diseases, such as COVID-19, due to the beneficial impacts of exercise on the immune system. Preliminary result indicates that home-based exercise may be an essential component in future physical activity recommendations given the current COVID-19 pandemic and the need for social distancing. This home-based physical exercise can be easily regulated and monitored using step counters and activity trackers, enabling individuals to manage health issues that benefit from physical exercise.

14.
Nat Med ; 2021 Oct 25.
Article in English | MEDLINE | ID: covidwho-1483142

ABSTRACT

Emerging reports of rare neurological complications associated with COVID-19 infection and vaccinations are leading to regulatory, clinical and public health concerns. We undertook a self-controlled case series study to investigate hospital admissions from neurological complications in the 28 days after a first dose of ChAdOx1nCoV-19 (n = 20,417,752) or BNT162b2 (n = 12,134,782), and after a SARS-CoV-2-positive test (n = 2,005,280). There was an increased risk of Guillain-Barré syndrome (incidence rate ratio (IRR), 2.90; 95% confidence interval (CI): 2.15-3.92 at 15-21 days after vaccination) and Bell's palsy (IRR, 1.29; 95% CI: 1.08-1.56 at 15-21 days) with ChAdOx1nCoV-19. There was an increased risk of hemorrhagic stroke (IRR, 1.38; 95% CI: 1.12-1.71 at 15-21 days) with BNT162b2. An independent Scottish cohort provided further support for the association between ChAdOx1nCoV and Guillain-Barré syndrome (IRR, 2.32; 95% CI: 1.08-5.02 at 1-28 days). There was a substantially higher risk of all neurological outcomes in the 28 days after a positive SARS-CoV-2 test including Guillain-Barré syndrome (IRR, 5.25; 95% CI: 3.00-9.18). Overall, we estimated 38 excess cases of Guillain-Barré syndrome per 10 million people receiving ChAdOx1nCoV-19 and 145 excess cases per 10 million people after a positive SARS-CoV-2 test. In summary, although we find an increased risk of neurological complications in those who received COVID-19 vaccines, the risk of these complications is greater following a positive SARS-CoV-2 test.

15.
PLoS One ; 16(10): e0258689, 2021.
Article in English | MEDLINE | ID: covidwho-1477537

ABSTRACT

BACKGROUND: Data to better understand and manage the COVID-19 pandemic is urgently needed. However, there are gaps in information stored within even the best routinely-collected electronic health records (EHR) including test results, remote consultations for suspected COVID-19, shielding, physical activity, mental health, and undiagnosed or untested COVID-19 patients. Observational and Pragmatic Research Institute (OPRI) Singapore and Optimum Patient Care (OPC) UK established Platform C19, a research database combining EHR data and bespoke patient questionnaire. We describe the demographics, clinical characteristics, patient behavior, and impact of the COVID-19 pandemic using data within Platform C19. METHODS: EHR data from Platform C19 were extracted from 14 practices across UK participating in the OPC COVID-19 Quality Improvement program on a continuous, monthly basis. Starting 7th August 2020, consenting patients aged 18-85 years were invited in waves to fill an online questionnaire. Descriptive statistics were summarized using all data available up to 22nd January 2021. FINDINGS: From 129,978 invitees, 31,033 responded. Respondents were predominantly female (59.6%), white (93.5%), and current or ex-smokers (52.6%). Testing for COVID-19 was received by 23.8% of respondents, of which 7.9% received positive results. COVID-19 symptoms lasted ≥4 weeks in 19.5% of COVID-19 positive respondents. Up to 39% respondents reported a negative impact on questions regarding their mental health. Most (67%-76%) respondents with asthma, Chronic Obstructive Pulmonary Disease (COPD), diabetes, heart, or kidney disease reported no change in the condition of their diseases. INTERPRETATION: Platform C19 will enable research on key questions relating to COVID-19 pandemic not possible using EHR data alone.


Subject(s)
COVID-19 , Databases, Factual , Electronic Health Records , Primary Health Care , SARS-CoV-2 , Adolescent , Adult , Aged , COVID-19/epidemiology , COVID-19/therapy , Female , Humans , Male , Middle Aged , United Kingdom/epidemiology
16.
Diabetes Care ; 2021 Oct 08.
Article in English | MEDLINE | ID: covidwho-1463413

ABSTRACT

Certain chronic comorbidities, including diabetes, are highly prevalent in people with coronavirus disease 2019 (COVID-19) and are associated with an increased risk of severe COVID-19 and mortality. Mild glucose elevations are also common in COVID-19 patients and associated with worse outcomes even in people without diabetes. Several studies have recently reported new-onset diabetes associated with COVID-19. The phenomenon of new-onset diabetes following admission to the hospital has been observed previously with other viral infections and acute illnesses. The precise mechanisms for new-onset diabetes in people with COVID-19 are not known, but it is likely that a number of complex interrelated processes are involved, including previously undiagnosed diabetes, stress hyperglycemia, steroid-induced hyperglycemia, and direct or indirect effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on the ß-cell. There is an urgent need for research to help guide management pathways for these patients. In view of increased mortality in people with new-onset diabetes, hospital protocols should include efforts to recognize and manage acute hyperglycemia, including diabetic ketoacidosis, in people admitted to the hospital. Whether new-onset diabetes is likely to remain permanent is not known, as the long-term follow-up of these patients is limited. Prospective studies of metabolism in the setting of postacute COVID-19 will be required to understand the etiology, prognosis, and treatment opportunities.

17.
Lancet Reg Health Eur ; 9: 100180, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1461657

ABSTRACT

Background: In most countries, healthcare workers (HCWs) represent a priority group for vaccination against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) due to their elevated risk of COVID-19 and potential contribution to nosocomial SARS-CoV-2 transmission. Concerns have been raised that HCWs from ethnic minority groups are more likely to be vaccine hesitant (defined by the World Health Organisation as refusing or delaying a vaccination) than those of White ethnicity, but there are limited data on SARS-CoV-2 vaccine hesitancy and its predictors in UK HCWs. Methods: Nationwide prospective cohort study and qualitative study in a multi-ethnic cohort of clinical and non-clinical UK HCWs. We analysed ethnic differences in SARS-CoV-2 vaccine hesitancy adjusting for demographics, vaccine trust, and perceived risk of COVID-19. We explored reasons for hesitancy in qualitative data using a framework analysis. Findings: 11,584 HCWs were included in the cohort analysis. 23% (2704) reported vaccine hesitancy. Compared to White British HCWs (21.3% hesitant), HCWs from Black Caribbean (54.2%), Mixed White and Black Caribbean (38.1%), Black African (34.4%), Chinese (33.1%), Pakistani (30.4%), and White Other (28.7%) ethnic groups were significantly more likely to be hesitant. In adjusted analysis, Black Caribbean (aOR 3.37, 95% CI 2.11 - 5.37), Black African (aOR 2.05, 95% CI 1.49 - 2.82), White Other ethnic groups (aOR 1.48, 95% CI 1.19 - 1.84) were significantly more likely to be hesitant. Other independent predictors of hesitancy were younger age, female sex, higher score on a COVID-19 conspiracy beliefs scale, lower trust in employer, lack of influenza vaccine uptake in the previous season, previous COVID-19, and pregnancy. Qualitative data from 99 participants identified the following contributors to hesitancy: lack of trust in government and employers, safety concerns due to the speed of vaccine development, lack of ethnic diversity in vaccine studies, and confusing and conflicting information. Participants felt uptake in ethnic minority communities might be improved through inclusive communication, involving HCWs in the vaccine rollout, and promoting vaccination through trusted networks. Interpretation: Despite increased risk of COVID-19, HCWs from some ethnic minority groups are more likely to be vaccine hesitant than their White British colleagues. Strategies to build trust and dispel myths surrounding the COVID-19 vaccine in these communities are urgently required. Emphasis should be placed on the safety and benefit of SARS-CoV-2 vaccination in pregnancy and in those with previous COVID-19. Public health communications should be inclusive, non-stigmatising and utilise trusted networks. Funding: UKRI-MRC and NIHR.

18.
BMC Infect Dis ; 21(1): 908, 2021 Sep 04.
Article in English | MEDLINE | ID: covidwho-1455937

ABSTRACT

BACKGROUND: Pre-existing comorbidities have been linked to SARS-CoV-2 infection but evidence is sparse on the importance and pattern of multimorbidity (2 or more conditions) and severity of infection indicated by hospitalisation or mortality. We aimed to use a multimorbidity index developed specifically for COVID-19 to investigate the association between multimorbidity and risk of severe SARS-CoV-2 infection. METHODS: We used data from the UK Biobank linked to laboratory confirmed test results for SARS-CoV-2 infection and mortality data from Public Health England between March 16 and July 26, 2020. By reviewing the current literature on COVID-19 we derived a multimorbidity index including: (1) angina; (2) asthma; (3) atrial fibrillation; (4) cancer; (5) chronic kidney disease; (6) chronic obstructive pulmonary disease; (7) diabetes mellitus; (8) heart failure; (9) hypertension; (10) myocardial infarction; (11) peripheral vascular disease; (12) stroke. Adjusted logistic regression models were used to assess the association between multimorbidity and risk of severe SARS-CoV-2 infection (hospitalisation/death). Potential effect modifiers of the association were assessed: age, sex, ethnicity, deprivation, smoking status, body mass index, air pollution, 25-hydroxyvitamin D, cardiorespiratory fitness, high sensitivity C-reactive protein. RESULTS: Among 360,283 participants, the median age was 68 [range 48-85] years, most were White (94.5%), and 1706 had severe SARS-CoV-2 infection. The prevalence of multimorbidity was more than double in those with severe SARS-CoV-2 infection (25%) compared to those without (11%), and clusters of several multimorbidities were more common in those with severe SARS-CoV-2 infection. The most common clusters with severe SARS-CoV-2 infection were stroke with hypertension (79% of those with stroke had hypertension); diabetes and hypertension (72%); and chronic kidney disease and hypertension (68%). Multimorbidity was independently associated with a greater risk of severe SARS-CoV-2 infection (adjusted odds ratio 1.91 [95% confidence interval 1.70, 2.15] compared to no multimorbidity). The risk remained consistent across potential effect modifiers, except for greater risk among older age. The highest risk of severe infection was strongly evidenced in those with CKD and diabetes (4.93 [95% CI 3.36, 7.22]). CONCLUSION: The multimorbidity index may help identify individuals at higher risk for severe COVID-19 outcomes and provide guidance for tailoring effective treatment.


Subject(s)
COVID-19 , SARS-CoV-2 , Aged , Aged, 80 and over , Hospitalization , Humans , Middle Aged , Multimorbidity , Risk Factors
19.
Diabetes ; 69:N.PAG-N.PAG, 2020.
Article in English | Academic Search Complete | ID: covidwho-1456236

ABSTRACT

Background: DISCOVER is a 3-year, observational study of people with type 2 diabetes (T2D) initiating a second-line glucose-lowering therapy in 38 countries. We assessed glycemic control after 3 years in participants with HbA1c ≥ 9.0% at baseline. Methods: Factors associated with an increased likelihood of having HbA1c < 7.0% after 3 years were assessed using a hierarchical logistic regression model. Results: Of 14 691 DISCOVER participants from 37 countries, 2233 (15.2%) had sufficient HbA1c data and HbA1c ≥ 9.0% at baseline. The majority of participants were men (58.0%), and the mean age was 54.4 years (SD: 11.2 years). The mean HbA1c at baseline was 10.4% (SD: 1.4%). After 3 years, 626 participants (28.0%) had HbA1c < 7.0% and 438 (19.6%) had HbA1c ≥ 9.0%. Time since T2D diagnosis ≥ 10 years (vs.< 5 years) was associated with a decreased likelihood of having HbA1c < 7.0% at 3 years (Figure). Second-line therapy with two or more glucose-lowering drugs (vs. insulin) and having HbA1c < 7.0% at 6 months (24.2% of patients) were associated with an increased likelihood of having HbA1c < 7.0% at 3 years. Conclusions: Less than a third of participants with HbA1c ≥ 9.0% at initiation of second-line therapy reached HbA1c < 7.0% after 3 years. Early glycemic control (HbA1c < 7.0% at 6 months) was a key factor associated with attaining this target. Disclosure: F. Bonnet: Consultant;Self;Amgen, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi-Aventis. H. Chen: None. A. Cooper: Employee;Self;AstraZeneca. M.B. Gomes: None. L. Ji: None. P. Leigh: Employee;Self;AstraZeneca. Employee;Spouse/Partner;Merck Sharp & Dohme Corp. L. Ramirez Gutierrez: None. M.V. Shestakova: None. I. Shimomura: Advisory Panel;Self;AstraZeneca K.K., Daiichi Sankyo, Novo Nordisk Pharma Ltd., Taisho Pharmaceutical Co., Ltd. Consultant;Self;MSD K.K., Novo Nordisk Pharma Ltd. Research Support;Self;Astellas Pharma Inc., Daiichi Sankyo, Eli Lilly Japan K.K., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Mitsubishi Tanabe Pharma Corporation, MSD K.K., Novartis Pharma K.K., Novo Nordisk Pharma Ltd., Ono Pharmaceutical Co., Ltd., Sanofi K.K., Sumitomo Dainippon Pharma Co., Ltd., Takeda Pharmaceutical Company Limited, Teijin Pharma Limited. Speaker's Bureau;Self;Amgen Astellas BioPharma K.K., Astellas Pharma Inc., AstraZeneca K.K., Covidien Japan Inc., Daiichi Sankyo, Eli Lilly Japan K.K., KOBAYASHI Pharmaceutical Co., Ltd., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Mitsubishi Tanabe Pharma Corporation, MSD K.K., Nippon Boehringer Ingelheim Co. Ltd., Nippon Chemiphar Co., Ltd., Novo Nordisk Pharma Ltd., Ono Pharmaceutical Co., Ltd., Rohto Pharmaceutical Co., Ltd., Sanofi K.K., Sanwa Kagaku Kenkyusho, Sumitomo Dainippon Pharma Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Company Limited, Teijin Pharma Limited. A. Siddiqui: None. F. Tang: Research Support;Self;AstraZeneca. J. Vora: Other Relationship;Self;AstraZeneca. H. Watada: Advisory Panel;Self;Abbott, Ajinomoto, Astellas Pharma Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Fuji Film, Janssen Pharmaceuticals, Inc., Kowa Company, Ltd., Kyowa Hakko Kirin Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Novo Nordisk Inc., Ono Pharmaceutical Co., Ltd., Sanofi-Aventis, Takeda Pharmaceutical Company Limited, Terumo Medical Corporation. Research Support;Self;Astellas Pharma Inc., Bayer Yakuhin, Ltd., Boehringer Ingelheim Pharmaceuticals, Inc., Daiichi Sankyo, Eli Lilly Japan K.K., Kissei Pharmaceutical Co., Ltd., Kowa Company, Ltd., Kyowa Hakko Kirin Co., Ltd., Merck Sharp & Dohme Corp., Mitsubishi Tanabe Pharma Corporation, Novartis Pharma K.K., Novo Nordisk Inc., Ono Pharmaceutical Co., Ltd., Otsuka Pharmaceutical Co., Ltd., Pfizer Japan Inc., Sanofi-Aventis, Sanwa Kagaku Kenkyusho, Shionogi & Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Company Limited, Teijin Pharma Limited, Yakult. Speaker's Bureau;Self;stellas Pharma Inc., AstraZeneca, Bayer Yakuhin, Ltd., Boehringer Ingelheim Pharmaceuticals, Inc., Daiichi Sankyo, Eli Lilly Japan K.K., Kissei Pharmaceutical Co., Ltd., Kowa Company, Ltd., Kyowa Hakko Kirin Co., Ltd., Merck Sharp & Dohme Corp., Mitsubishi Tanabe Pharma Corporation, Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Ono Pharmaceutical Co., Ltd., Sanofi-Aventis, Sanwa Kagaku Kenkyusho, Sumitomo Dainippon Pharma Co., Ltd., Takeda Pharmaceutical Company Limited. K. Khunti: Advisory Panel;Self;Amgen, AstraZeneca, Bayer AG, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Menarini Group, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi-Aventis, Servier. Board Member;Self;AstraZeneca, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi-Aventis. Consultant;Self;Amgen, AstraZeneca, Bayer AG, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Menarini Group, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi-Aventis, Servier. Research Support;Self;AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis AG, Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis, Servier. Speaker's Bureau;Self;Amgen, AstraZeneca, Bayer AG, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Menarini Group, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi-Aventis, Servier. Funding: AstraZeneca [ABSTRACT FROM AUTHOR] Copyright of Diabetes is the property of American Diabetes Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

20.
Diabetes ; 69:N.PAG-N.PAG, 2020.
Article in English | Academic Search Complete | ID: covidwho-1456231

ABSTRACT

Background: Symptom relief, prolonging survival and avoiding complications are key goals in treating type 2 diabetes (T2D), but health-related quality of life (HRQoL) may be as or more important to patients. We used DISCOVER, a global observational study of people with T2D initiating a second-line glucose-lowering therapy, to examine factors associated with HRQoL over 3 years of follow-up. Methods: HRQoL was assessed using the 36-item Short-Form Health Survey (SF-36) v2 mental and physical component summary (MCS;PCS) scores (higher scores = better HRQoL) and the Hypoglycemia Fear Survey II (HFS-II;higher scores = greater fear). Factors associated with HRQoL over time were assessed using longitudinal multivariable regression models. Results: Of 14 691 DISCOVER patients from 37 countries, baseline and ≥ 1 follow-up MCS, PCS and HFS-II scores were available for 7880, 7854 and 5387 patients, respectively. Over time, SF-36 scores decreased (change per 6 months from baseline: MCS −0.04 [95% CI: −0.05 to −0.04];PCS −0.03 [95% CI: −0.03 to −0.02]), and HFS-II scores increased (change: 0.10 [95% CI: 0.09 to 0.12]). Many factors were associated with HRQoL (Table). Conclusions: HRQoL worsened during follow-up. Patient-, disease- and treatment-related factors were associated with HRQoL differences. Assessing factors associated with HRQoL over time may inform interventions to improve this important outcome. Disclosure: A. Nicolucci: Consultant;Self;AstraZeneca. H. Chen: None. A. Cooper: Employee;Self;AstraZeneca. M.B. Gomes: None. L. Ji: None. K. Khunti: Advisory Panel;Self;Amgen, AstraZeneca, Bayer AG, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Menarini Group, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi-Aventis, Servier. Board Member;Self;AstraZeneca, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi-Aventis. Consultant;Self;Amgen, AstraZeneca, Bayer AG, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Menarini Group, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi-Aventis, Servier. Research Support;Self;AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis AG, Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis, Servier. Speaker's Bureau;Self;Amgen, AstraZeneca, Bayer AG, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Menarini Group, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi-Aventis, Servier. M.N. Kosiborod: Consultant;Self;Amarin Corporation, Amgen, Applied Therapeutics, AstraZeneca, Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc., Eisai Inc., Eli Lilly and Company, GlaxoSmithKline plc., Glytec, Intarcia Therapeutics, Janssen Scientific Affairs, LLC., Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Sanofi US, Vifor Pharma Group. Research Support;Self;AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc. P. Leigh: Employee;Self;AstraZeneca. Employee;Spouse/Partner;Merck Sharp & Dohme Corp. L. Ramirez: None. M.V. Shestakova: None. I. Shimomura: Advisory Panel;Self;AstraZeneca K.K., Daiichi Sankyo, Novo Nordisk Pharma Ltd., Taisho Pharmaceutical Co., Ltd. Consultant;Self;MSD K.K., Novo Nordisk Pharma Ltd. Research Support;Self;Astellas Pharma Inc., Daiichi Sankyo, Eli Lilly Japan K.K., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Mitsubishi Tanabe Pharma Corporation, MSD K.K., Novartis Pharma K.K., Novo Nordisk Pharma Ltd., Ono Pharmaceutical Co., Ltd., Sanofi K.K., Sumitomo Dainippon Pharma Co., Ltd., Takeda Pharmaceutical Company Limited, Teijin Pharma Limited. Speaker's Bureau;Self;Amgen Astellas BioPharma K.K., Astellas Pharma Inc., AstraZeneca K.K., Covidien Japan Inc., Daiichi Sankyo, Eli Lilly Japan K.K., KOBAYASHI Pharmaceutical Co., Ltd., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Mitsubishi T nabe Pharma Corporation, MSD K.K., Nippon Boehringer Ingelheim Co. Ltd., Nippon Chemiphar Co., Ltd., Novo Nordisk Pharma Ltd., Ono Pharmaceutical Co., Ltd., Rohto Pharmaceutical Co., Ltd., Sanofi K.K., Sanwa Kagaku Kenkyusho, Sumitomo Dainippon Pharma Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Company Limited, Teijin Pharma Limited. A. Siddiqui: None. F. Tang: Research Support;Self;AstraZeneca. J. Vora: Other Relationship;Self;AstraZeneca. H. Watada: Advisory Panel;Self;Abbott, Ajinomoto, Astellas Pharma Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Fuji Film, Janssen Pharmaceuticals, Inc., Kowa Company, Ltd., Kyowa Hakko Kirin Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Novo Nordisk Inc., Ono Pharmaceutical Co., Ltd., Sanofi-Aventis, Takeda Pharmaceutical Company Limited, Terumo Medical Corporation. Research Support;Self;Astellas Pharma Inc., Bayer Yakuhin, Ltd., Boehringer Ingelheim Pharmaceuticals, Inc., Daiichi Sankyo, Eli Lilly Japan K.K., Kissei Pharmaceutical Co., Ltd., Kowa Company, Ltd., Kyowa Hakko Kirin Co., Ltd., Merck Sharp & Dohme Corp., Mitsubishi Tanabe Pharma Corporation, Novartis Pharma K.K., Novo Nordisk Inc., Ono Pharmaceutical Co., Ltd., Otsuka Pharmaceutical Co., Ltd., Pfizer Japan Inc., Sanofi-Aventis, Sanwa Kagaku Kenkyusho, Shionogi & Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Company Limited, Teijin Pharma Limited, Yakult. Speaker's Bureau;Self;Astellas Pharma Inc., AstraZeneca, Bayer Yakuhin, Ltd., Boehringer Ingelheim Pharmaceuticals, Inc., Daiichi Sankyo, Eli Lilly Japan K.K., Kissei Pharmaceutical Co., Ltd., Kowa Company, Ltd., Kyowa Hakko Kirin Co., Ltd., Merck Sharp & Dohme Corp., Mitsubishi Tanabe Pharma Corporation, Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Ono Pharmaceutical Co., Ltd., Sanofi-Aventis, Sanwa Kagaku Kenkyusho, Sumitomo Dainippon Pharma Co., Ltd., Takeda Pharmaceutical Company Limited. S.V. Arnold: None. Funding: AstraZeneca [ABSTRACT FROM AUTHOR] Copyright of Diabetes is the property of American Diabetes Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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